Brief: Do trust levels predict sexual activity among the young?

I'm becoming more convinced that the decline in trust levels during the late 1980s may have a lot to do with the decline starting a few years later in all sorts of risky behavior. The logic is simple: the more (or less) trusting you are of others, the more (or less) risk you're willing to take in social life, and also exploiters will have a more (or less) easy time finding "suckers." We looked before at homicide rates. Now let's turn to sexual activity among young people.

For trust levels, I use the General Social Survey's question on whether you think others can be trusted, and restricted respondents to those from 18 to 25 years old. The GSS doesn't survey minors, so I used this age range for "young people." The time series for trust doesn't seem to vary wildly based on which age range you restrict it to, so it seems OK to use trust levels among young adults as a proxy for trust levels among adolescents. For risky sexual activity, I use the pregnancy rate among females ages 15 to 17 (here), which are yearly from 1972 to 2006; and the percent of high schoolers who have had sex before age 13 (here), which are bi-yearly from 1991 to 2007. The trust data are from 1972 to 2008, and coverage is usually bi-yearly or more frequent.

Here are the results. Trust levels are in blue and sexual activity measures in red.



Although the relationship is not perfect, there's a close match overall, and the timing looks like the trust level changes first, followed by a change in sexual activity. That fits with trust being the cause and risky behavior the effect. The correlation across years between trust and the pregnancy rate is +0.47, and between trust and the early sex rate it is +0.44. The Youth Risk Behavior Survey that I got the early sex rate data from has three other measures of teenage sexual activity, and the relationships are similar but not quite as strong.

The correlations with trust are: +0.15 for percent of high schoolers who'd had sex at least once in the past 3 months; +0.21 for the percent who've had 4+ partners in their life; and +0.23 for the percent who've ever had sex. * I also created an index of young sexual activity, which is just the sum of the fraction of students responding positively to each of the 4 questions. This is the expected number of "yes" answers that a high schooler would give while reading off the check-list of risky sex behaviors. The correlation between this index and trust is +0.25.

In general, I think these correlations are weaker just because there are fewer data -- 1991 to 2007, every other year -- than in the case of pregnancy rates. I suspect that the pre-1991 picture for the 4 behaviors surveyed in the YRBS would have looked highly similar to the teen pregnancy rate, so if we had those data, they would probably make the pattern even stronger. In any case, it seems clear that, while not the entire story, how trusting people are of one another plays a substantial role in how willing young people are to engage in risky sexual behavior. That's not too surprising if we think of trust as a form of insurance, but it's still something that's been completely overlooked as far as I know from the social science lit on these two topics that have previously been studied independently of each other.

If I can find good data on cross-national differences in number of lifetime sex partners, or other measure of promiscuity, I might use the national trust level data from the World Values Survey and turn this into a fuller post. It depends on how easy the former data are to get. Informally, though, my impression is that the low-trust countries are more sexually conservative, while the high-trust ones are more sexually liberal.

* The sexual activity correlations paired the sex activity variable and trust variable for the same year if possible (for 1991 and 1993), but since the data use different sets of alternate years after that, I paired the sex variable in a certain year with the trust variable in the following year.

GSS variables used: trust, age, year

Brief: Did third-wave feminism ruin Gen-X guys' sex lives?

There was a society-wide hysteria that reached a fever pitch in 1991, encompassing the rebirth of identity politics, feminism ("third-wave"), gay rights, and political correctness in general. The panic was still pretty high through 1994, although it died off afterward. Compared to second-wave feminism -- which focused more on equal pay, a lower housework burden, and so on -- third-wave feminism was much more focused on sexual harassment, rape, male libido, etc.

Was all that paranoia about all men being crypto-rapists just cheap talk, or did it have real consequences for the relation between the sexes? An easy way to test this is to look at how likely men were to remain virgins after graduating college through their 20s. I used the General Social Survey to focus on males aged 21 to 29 when they were surveyed. I grouped them into 3-year birth cohorts, except for the last one, where a tiny number of late-'80s males were lumped into the previous cohort just to make the sample sizes better.

Here is the percent of 20-something respondents who said they'd had 0 female partners since turning 18 -- which in context I take to mean 0 partners ever -- shown by the middle year of the 3-year cohort (or by 1986 for the '84-'89 cohort):


The long-term trend looks like between 6% and 7% fall into the 20-something virgin group. The early-'60s cohort is much lower, which makes sense because that cohort was completely unaffected by feminist hysteria. They were born too late to come of age during the counter-culture and too soon to come of age during the early-'90s hysteria. As I've pointed out elsewhere on this blog, the late '70s and early '80s were a remarkably non-ideological and hysteria-free period. However, those who came of age during the early-'90s hysteria show much higher rates of virginity in their 20s -- about double the long-term trend, or 5 to 6 percentage points higher. The effect even lasts through those who came of age in the mid-'90s, although their departure from the trend isn't so extreme. It isn't until those who were born in the early '80s, who came of age in the late-'90s or later, that the rate returns to the trend.

People often poo-poo the framework of generations -- there's so much variation within generations, not as much across generations, no sharp changes, etc. Well here's a very clear demonstration of an abrupt and gigantic change in a key rite of passage for males, and the timing is not mysterious given what we know about larger cultural changes afoot in the early-'90s. This also supports my approach to see generations as a cohort of vulnerable individuals who are struck by a huge but passing hysteria (a shock to the social system). There's some age range in which people are vulnerable to bearing the scars of the hysteria -- not younger or older -- and those indelibe impressions cause a lot of them to look similar to each other and different from other groups. That's why you can still tell who was coming of age during the counter-culture even though that was 40 years ago.

GSS variables used: numwomen, cohort, sex, age

Just how permissive are the beliefs of non-heterosexuals?

Studies of gay and bisexual men show that they are more sexually permissive in their behavior, and likewise for bisexual women compared to straight or lesbian women. But sexual behavior is always constrained by the simple fact that it takes two. Why don't we look at their beliefs on sexually permissive behavior, which might give us a purer view of the differences between heterosexuals and non-heterosexuals.

(I collapse gay and bisexual males into a single non-heterosexual group, but preserve the three-part division among females, because that's what the findings on arousal argue for. Men are aroused either by male or female erotic images, but not by both; whereas some women truly are aroused by both.)

We will treat "sexual permissiveness" as a personality trait or preference that's too tough to measure precisely, but that we can investigate using La Griffe du Lion's method of thresholds. We imagine sexual permissiveness as a continuous trait -- some people score really low, others really high, and everything in between. At some point toward the high-end of this spectrum, we set a threshold and ask what percent of the various groups score above that threshold? We can then use this to figure out how far apart the average scores of the various groups are, assuming the trait to be normally distributed. Knowing that, we can also predict what ratio of one group to another we would expect at some extreme value of the trait -- far out into the right tail.

To identify a clearly high-end threshold for sexual permissiveness, consider what your beliefs are about two 14 to 16 year-olds having sex. The General Social Survey asks just such a question: is it always wrong, almost always wrong, sometimes wrong, or not wrong at all? As you look at higher values of sexual permissiveness, at some point you reach the value where the person is permissive enough to think that teenage sex is OK (maybe with provisos) rather than always wrong. Here is a picture to help see what I mean:


Along the spectrum of permissiveness, at the low end we find people who believe that oral sex is OK -- people whose value is to the left of that point are not even that permissive -- while farther to the right, we find people who are permissive enough to believe that teenage sex is OK. Farther to the right still, we find people with ever more permissive beliefs, perhaps going so far as to condone public unprotected sex. A group of people will have a distribution of values along this spectrum, and we'll assume it's normal for convenience and because most personality traits are made to be normal too. We also assume the various groups have the same variance.

By finding out what percent of some group lies to the right of our threshold point, we can work backward to determine what z-score this threshold represents for the group. Doing this for two groups, we can find the difference between the means of each. For example, if 16% of group A exceeds the threshold, while just 2.5% of group B exceeds the threshold, that implies that the threshold is +1 S.D. above A's mean and +2 S.D. above B's mean. That means that there is a difference of 2 - 1 = 1 S.D. between the two group's means, favoring A.

Furthermore, knowing how far apart the two groups are on average, we can extrapolate what the A-to-B ratio would be at an even further extreme value that we haven't even observed. Obviously there will be more A's than B's (if the two groups are the same size), but the question is by how much. These extreme value predictions are useful because we find extremes more fascinating than averages, and it may be harder to get honest answers out of people as we ask more and more extreme questions.

Now back to sexual permissiveness. The GSS allows two ways to figure out who is heterosexual or not. One is straightforward and asks what sex your sex partners have been over the last 5 years: only male, male and female, or only female. They also ask how many male (or female) partners you've had since age 18. If a male answers 0 partners, he's straight; if he answers 1 or more, he's not. You can do the same for females; bisexuals have to answer 1 or more partners for both questions. The sample sizes are a bit larger using the second method, but the results are very similar. So I'll show the graphs for both methods, but I'll only use the second one in applying the method of thresholds.

First, here are the graphs for male heterosexuals vs. non-heterosexuals, for the first and then second method:



Straight males are more likely to say teenage sex is always wrong, while gay males are more permissive -- although a bare majority of them still think it's always wrong. Next, the differences among females for the first and then second method:



Notice first that females overall are less permissive than males -- no surprise there. Lesbians are more permissive than straight females, but not nearly by the same gap as the one separating gay and straight males. However, there is a yawning chasm separating bisexual females not only from the other female groups but even from both male groups! This result about their beliefs is consistent with their sexual behavior, as surveys (including the GSS) routinely show that bisexual females lead over-sexed lives. They have a general "wild child" mindset, so it shouldn't be surprising that those who think teenage sex is always wrong are in the minority among bisexual women.

(I've looked at responses to this teenage sex question across all sorts of demographic groups, and aside from GSS respondents who are youngsters themselves, I haven't found a single group where the majority think it is OK, let alone one where one estimate puts them at over 60%. Very wild indeed.)

Comparing gay to straight males, we find a difference in means of 0.31 S.D. favoring gay males. Comparing lesbian to straight females, there is a 0.17 S.D. gap favoring lesbians. And comparing bisexual to straight females, there is a 0.68 S.D. gap favoring bisexuals. To make this more intuitive, let's pretend we were talking about height instead of sexual permissiveness. It's as if gay men were 0.92 inches "taller" than straight men on average; as if lesbians were 0.51 inches "taller" than straight women on average; and as if bisexual women were 2 inches "taller" than straight women on average. You might notice the gay-straight gap in the real world, probably not the lesbian-straight gap, but almost certainly you'd notice the bisexual-straight gap.

Now suppose we wanted to predict how much one group would predominate at an even more extreme value along the permissiveness spectrum. That might be holding the belief that it's OK to have unprotected sex in public -- or actually having done so. These extremes are harder to investigate directly because the events that would tip us off to people being there are incredibly rare, and asking people if they've ever had unprotected sex in public may not give us very reliable answers. So we turn to the method of thresholds and ask what ratio of non-heterosexuals to heterosexuals we predict to find at, say, the value of 3 S.D. above the heterosexual average.

Obviously this won't tell us what to expect in the real world since the straight and non-straight populations are very different in size. Still, we'll pretend they were the same size in order to highlight how different the various groups are. In a moment, I'll re-adjust these ratios to reflect the groups' real sizes in order to get better real-world predictions.

At the extreme value of 3 S.D. above the straight male mean, we expect a gay-to-straight ratio of 2.6 to 1. At the value of 3 S.D. above the straight female mean, we expect a lesbian-to-straight ratio of 1.7 to 1, and a bisexual-to-straight ratio of 7.6 to 1! Clearly the minds of heterosexuals and non-heterosexuals are not the same on average.

Correcting for the huge differences in population size between straights and non-straights, I've used the GSS to figure out what percent of the male and female population are gay, straight, or bisexual. For males, 96% are straight and 4% gay. For females, 96.4% are straight, 2% are lesbian, and 1.6% are bisexual. In the real world, then, we expect 9.2 straight males for every gay male at the extreme; 28.1 straight females for every lesbian; and 8 straight females for every bisexual female. The larger point remains, though: non-heterosexuals, especially bisexual women, are more permissive in the beliefs -- and so presumably in their actions -- than heterosexuals.

As an analogy, consider the fact that Ashkenazi Jewish people score much higher (about 1 S.D.) on IQ tests than other Europeans. Still, because Jews make up such a small fraction of the overall population (about 2%), it will still be the case that non-Jewish Europeans will outnumber Jews at extreme IQ levels. The first fact tells us that a representative person from the two groups will be pretty different, perhaps due to their ancestors facing different evolutionary selection pressures or due to having different hormone levels or whatever. The second fact tells us that we shouldn't let the first fact lead us to expect a majority of the unusual group at unusual levels, unless the two groups are similar in size.

GSS variables used: teensex, sex, sexsex5, nummen, numwomen

Diversity in aesthetic tastes over the last 130 years: Evidence from names

Updated

Virginia Postrel argues in The Substance of Style that we have entered a new aesthetic age, where design objects are available to a mass audience, where those consumers no longer consider just the price but also the look and feel of the stuff they buy, and so where producers don't compete with each other only on price but also on how aesthetically pleasing their products are. (Think of how many stylish toilet brushes you can buy at Wal-Mart or Target.)

She wrote this in 2003 and claims it began sometime in the mid-to-late 1990s. That trend seemed to take off even more during the recent financial euphoria, and although it's surely taking a beating during the recession, it'll be back once we feel safe spending again.

One thing I kept asking myself was, "Is this really so new?" As a general rule, you should be skeptical of all stories about how we're "entering a new age." After all, what about the 1920s and '30s, which Postrel admits could have been a previous age of aesthetics? She counters that design wasn't enjoyed by nearly as large a fraction of the population as it is today, and that the range of products that were designed with aesthetics in mind also was more limited than today. What about the more mass-market design of the 1950s and '60s? She says that the choices available weren't nearly as varied and driven by customization as the ones we have today.

I've decided to take a different approach by looking at baby names, a program pioneered by Stanley Lieberson to investigate fashions (summarized in his excellent book A Matter of Taste). Unlike toilet brushes, cars, or paintings, names you give your baby don't cost money. They carry non-monetary costs -- you wouldn't name your kid Adolf, and it's not because you'd have to plunk down big bucks to register that name. Still, they are a lot closer to the ideal test of someone's desires where you ask them to "pretend that price isn't an issue."

Postrel sees the choice to endow an object with aesthetic qualities as "making it special." That has two consequences: it will tend to create turnover, as people start to make things special by making them different from what they were like yesterday; and it will tend to make things more diverse, as individuals try to look different from each other today. Lieberson has already provided graphs from many European countries on the turnover in names over time, going back centuries. The take-home message is that roughly before the industrial era, there was little to no turnover in names. (He measures turnover as the number of names in this year's Top 10 that were not present in last year's Top 10.) With industrialization, the fashion in names took off. The turnover rate really shoots up sometime in the mid-20th C., but it's not clear if it's something different or just the rapid-growth phase of a single, sustained exponential increase.

That's not too surprising, and it underscores the importance of not believing in "new era" stories. To a first approximation, there was the transition to agriculture, and then the transition to industrial capitalism -- and that's it. That's basically all we see in Lieberson's turnover data -- there is a pre-industrial stage with no turnover and an industrial stage with high turnover, and that's about all.

What about the diversity of names? Even if there were no turnover in the Top 10 names, we could still see people introducing more and more new names in order to make their children special. Recall that a big part of Postrel's story is that in our new aesthetic age, we really value standing out from others at the same point in time, not simply moving from one universal style to another over time. Lieberson does have some graphs on how highly concentrated names are, but the data are much more regional than national, they only cover some of the 20th C (although a decent chunk of it), and the measure isn't as precise as it could be. (He uses the percent of all names that are held by the Top 20 names, as well as the percent of all names that are given to only one person.) The rough pattern is that diversity of names seems somewhat static from roughly 1920 through either 1945 or 1960, and by no later than 1960 we see a tendency toward greater diversity.

To solve these problems somewhat, I turn to the Social Security Administration's archive of popular baby names. These are national data, so the sample size is a lot larger than Lieberson's regional data, and the regional differences are smoothed out. They also cover more time -- 1880 to 2008. And I've used a more standard measure of variation when the data are not quantitative (like names), as well as develop a measure of my own that is more flexible.

The standard measure I use is one of many ways to measure "qualitative variation," where the data are not numbers. It is thus impossible to compute how far a given datum deviates from the mean, and thus impossible to compute the variance. For data that are numbers -- height, IQ, etc. -- the variance tells us how spread out vs. how similar the values are. In the Appendix, I discuss what the two measures I use are, the standard one and my own. The only thing you need to know is that bigger values mean greater diversity.

With that out of the way, let's see what the historical pattern of conformity vs. diversity has been in aesthetic tastes. There are separate data for males and females, so I also show what the female - male gap has been:




First, note that the female line is always above the male line, a pattern that shows up in Lieberson's turnover data too. Parents give greater fashionableness to their daughters' names, and are less enthusiastic about their sons standing out.

There certainly has been a sharp increase during the past generation, starting around 1983 for boys and 1987 for girls. But that's nothing new. There was a more modest upturn from just after WWII until the early-mid 1980s. Moreover, there was another pronounced increase going back at least to 1880 (and probably before -- remember that the turnover data tracked industrialization), which fizzled out around 1905 for girls and 1910 for boys. From then until the post-WWII era, diversity actually stagnated or slightly declined. This trend obviously goes against what we'd expect from our view of the 1920s and '30s as a previous age of aesthetics. At least in the sense of "making special" as distinguishing things from one another in the same time period, the turn-of-the-century through the post-WWII era was conformist compared to the dizzying changes of the earlier industrializing stage or the turbulence that would follow.

In looking at the female - male gap, we are looking at another facet of culture -- namely, how egalitarian-minded people were with respect to sex (and perhaps in general). We see a narrowing of the gap from at least as far back as 1880 until 1915. From then until 1969, we see a general widening of the gap, although there are noticeable egalitarian dips during the depth of the Great Depression in the early-mid 1930s and during WWII. From 1915 until WWII, the widening gap is caused by boys receiving more similar names, with little change among girls. To me, that suggests traditionalism -- don't make girls' names any more fashionable, and drive boys names away from being fashion symbols.

From WWII to 1969, though -- i.e., during the Baby Boom -- the widening gap is caused by girls receiving more diverse names at a faster rate than boys are. This is a compromise between tradition and change -- clearly it's a break with the traditional values by making boys names more subject to fashion, but you don't notice it so much because girls' names are becoming even more subject to fashion.

Once the earliest Baby Boomers (born around 1945) reach child-bearing age (around 25), or in 1970, we see a steady reversal. Boomers wanted to equalize the outcomes of their own babies, and this was mostly due to slowing down the fashionableness of girls' names. That's what they tried elsewhere -- recognizing that females are more compliant than males, you should force females to be more like males rather than vice versa. Boomers were more likely to favor "bring your daughter to work day" than "give your son a dollhouse to play with."

There is a brief widening of the gap from 1987 to 1996, and this corresponds to the generation I've elsewhere called the disco-punk generation. They are too young to be canonical Boomers and too old to be Generation X-ers. I've estimated that they were born between about 1958 and 1964, so the typical member born in the early '60s would have started having kids in the late 1980s. This generation is very different from Boomers and X-ers, not having been ideological or attention-whoring when they were coming of age around 1980.

However, once the prototypical Gen X-er, born in 1971, starts having kids in 1997, the gap starts to close again. Remember, they were the ones who made Third Wave feminism a success.

So, the female - male gap shows us that our aesthetic preferences reflect larger social and cultural changes, such as how ideological we are about sex equality.

Even the overall data, which don't show such sensitivity to smaller-scale social changes, still reflect social change, although at a much larger level. The industrializing and globalizing stage was completed around the turn of the century. The change in the connectedness of the global economy was far greater from 1830 to 1920 than from 1920 to today. And most of the major innovations that came with industrialization were in place by then too. Those allowed design objects to reach a wider market, as well as greater customization with each passing year. We see this saturation of the industrial trends by the flat lines from roughly 1910 to 1945.

After WWII, we did start another round of changes away from manufacturing and toward services, and toward consumption of more "frivolous" goods and services than more basic ones, as the former became cheaper. What Postrel calls the new age of aesthetics really began in the mid-1980s, perhaps reflecting our greater taste for fashion items as we began to borrow more to buy more.

To conclude, we've found hard data showing that Postrel's hunch was right about the last generation being more and more aesthetically minded. But contrary to her "first time ever" theme, there was fantastic change during the industrializing stage too. Unfortunately the data don't go back to the beginning of that stage, which would probably show the trend even more clearly. But like I said before, that's the expected picture -- there's the shift to agriculture and the shift to industrial capitalism, and the rest are just hiccups.

Update: The historical pattern of rising diversity from the late 19th C through WWI, a stagnation or slight decline from then until WWII, and then another stage of sharp increase, mirrors the pattern of American openness to international trade. We became more integrated from the late 19th C through WWI, became more isolationist and protectionist from then until WWII, and then began reducing barriers to global trade. Perhaps there is some abstract "openness to differences" that characterizes the zeitgeist -- wanting to trade with people all over the world vs. economic nationalism, as well as wanting to explore a wider range of baby names vs. having more parochial tastes.

Appendix

Here are the graphs using the standard statistic. The patterns are harder to see because the lines have to obey a ceiling of 1, whereas the statistic I used lets them go wherever they want as long as they're not negative. The female - male gap doesn't reveal the influence of the disco-punk generation, but the other patterns are there.




The standard statistic is:

(N / (N - 1)) * (1 - sum((share)^2))

Here, N is the number of names. The Social Security Administration gives the top 1000 names, so it's 1000. A name's "share" is what fraction of the sample has that name. We square each name's share, add them up, subtract from one, and multiply by N / (N - 1). This gives us the probability that two randomly chosen individuals will have different names. If it's 0, everyone has the same name, while if it's 1, everyone has a unique name. I include the graphs based on this statistic as an appendix since they show roughly the same patterns but not as clearly, given how constrained the possible values are.

I don't like this statistic because it's forced to lie between 0 and 1, whereas the variance of a distribution just has to be non-negative. We want to let the measure grow infinitely large in order to capture cases where the data are that spread out. I made up my own statistic, but there are probably others like it out there already; not having a PhD in statistics, I don't know what they're called. The idea is similar to the first one. Start with the shares, and see what would happen at the two extremes of "everyone is the same" vs. "everyone is unique."

Like the inventors of the first statistic, I hit on the idea of squaring the shares and summing them up. (It's the obvious way to go if you start down this path.) With an infinitely large number of names, the extremes are 0 for all-unique and 1 for all-same. By taking the log of this, we get new extremes of negative infinity for all-unique and 0 for all-same. Multiply by -1, and they all become non-negative values that increase as the diversity increases, just like a variance is supposed to be:

- ln( sum ( (share)^2))

The sum of the squared shares is the probability that a randomly chosen pair share a name, and we'll just label that p. Then my statistic, which I call the name diversity index, is:

ln( 1 / p)

Again, the key is that it's 0 when everyone is the same and tends toward infinity when everyone is unique, just like variance.

Brief: Are Jews who marry outsiders duller?

For much of their history, Ashkenazi Jews practiced endogamous marriage, sticking mostly with their own. It was incredibly difficult to marry in, although nothing would prevent a person from leaving the group by marrying out. Given the almost exclusively white collar niche that they occupied for centuries, it is worth asking whether or not the Jews who left were duller than the ones who stayed -- perhaps they couldn't hack it as a tax farmer and moved on to being a potato farmer.

Obviously we cannot look up IQ data on Medieval Ashkenazi Jews, but we can at least look at contemporary American Jews to give us a hint. The General Social Survey asks questions about your religious preference and that of your spouse. I restricted respondents to only Jews and then looked at the mean IQ of Jews with Jewish spouses (endogamous) vs. Jews with non-Jewish spouses (exogamous). To get big sample sizes, I tried two different questions about your own religion -- what it is currently, and what it was at 16. The results are the same.

Endogamous Jews score 0.03 - 0.04 S.D. higher than exogamous Jews. That's an incredibly puny difference -- it's as if the endogamous were one-tenth of an inch taller than the exogamous on average. I looked at level of education, and that too looked similar.

But although endogamous Jews may not be much smarter than exogamous ones, they do earn more and are higher-status:




Neither group of Jews has many lower-class members, and they have the same proportion who are middle-class. However, 20% of exogamous Jews vs. 12% of endogamous Jews are working-class, and 7% of exogamous Jews vs. 17% of endogamous Jews are upper-class. As for income, both groups have similar proportions that earn less than $20K or more than $100K. However, 39% of exogamous Jews vs. 29% of endogamous Jews earn between $20K and $50K, and 26% of exogamous Jews vs. 33% of endogamous Jews earn between $50K and $100K. The median income for exogamous Jews is between $44K and $46K, while for endogamous Jews it is between $50K and $52K.

So, among contemporary Jews, those who marry within their group may not be smarter than those who leave, but they are wealthier and higher-status. Those who marry out, therefore, couldn't (or didn't want to) apply their equal level of intelligence to acquire as much material success as other Jews, and left for less competitive niches, brides with less lofty financial expectations, or something else.

Whether or not this is what happened when Ashkenazi Jews left their group to join their Eastern European host populations, we can't say for now. But it doesn't seem unreasonable -- only so many people can be high-status within a group, so the rest -- brainy or not -- will have to look elsewhere to find success. One big difference then was that wealth and status mattered a lot more for passing your genes throughout the generations, so -- if the current pattern held back then -- the endogamous Jews would have had a Darwinian advantage over the poorer ones who married out.

GSS variables used: sprel, relig, relig16, wordsum, educ, class, realinc

Brief: Do people vote selfishly when it comes to vices?

In Bryan Caplan's eye-opening book The Myth of the Rational Voter, he devotes some time to the literature showing that voters do not vote their narrow self interests. The well-to-do favor social safety net programs, men are typically more pro-choice, and so on. In general, people claim to and do vote for what they believe will make society better off. He says that the exceptions are personal vices, such as smokers being much more against smoking bans than are non-smokers. I went to the General Social Survey to see what other examples I could dig up on this pattern.

First:


Those who saw an x-rated movie last year, compared to those who didn't, are much more likely to want to keep pornography legal for adults, rather than ban it altogether.

Second:


Among married people, those who have cheated on their spouse are much more likely to want easier divorce laws. The idea is that if we had stricter laws, their vice could be more harshly punished, say by having to pay massive damages in divorce court if it were uncovered.

Next:


The more sex partners a woman has had in the past year, the more willing she is to support abortion for any reason whatsoever. The idea is that for such women, abortion is one form of birth control, and lacking this method of last resort would constrain their ability to indulge their vice of sleeping with a variety of men.

Finally, an exception to the "vice leads to selfish voting" rule:


These two graphs show that illegal drug users feel the same way as non-drug users about how well our drug policy is doing, rather than view it as too harsh or unjust, as we might have expected from the previous three cases. This case is different in that the vice is illegal, while the other three vices are perfectly legal. Obviously they could not vote selfishly because there are no "legalize it" pieces of legislation on the table.

But even when you just ask them their opinion, they still don't espouse the view that promotes their own self-interest. Perhaps the vices that we criminalize, on average, really are more harmful than those that we don't criminalize -- shooting heroin really is more ruinous than cheating, sleeping around, or watching porn. If that's so, then the heroin addict doesn't view his vice as something that's unobjectionable, and so doesn't view tough drug laws as an untenable constraint on his liberty, in the way that a porn addict would view his own vice and the attempts to criminalize it. He probably recognizes that shooting heroin is something that people should be protected from by making it harder to try out. The porn addict, by contrast, realizes that it never really hurt anyone, so people should not be protected from a false menace.

So, by experiencing how destructive illegal drugs are first-hand, users put on their "do what's best for society" hat and confess that current drug laws aren't as bad as ivory tower detractors might think. The other vices don't appear to destroy society, so those who indulge in them don't think about what's best for society -- you only get into that mindset when you perceive that something is a real problem that needs to be solved.

GSS variables used: pornlaw, xmovie, divlaw, evstray, abany, partners, sex, natdrug, hlth5, evidu

Brief: Are teachers more likely to be perverts?

One stereotype has it that adults who seek out jobs where they interact with teenagers all day every day are at least somewhat motivated by sexual desire. It raises our suspicions to see a 45 year-old man coaching a high school girls' soccer team, for instance.

The General Social Survey doesn't ask about the ages of the people you work with or are responsible for, but it does ask if you've volunteered in the education sector. If the above idea holds water, surely we should see it at work here. The GSS also asks whether you think pre-marital sex between two 14 - 16 year-olds is wrong or not. Surely those volunteering in education for ulterior motives would be more likely to say that it's OK. Here are the results of how wrong or right someone believes teen sex is, by whether or not they volunteered in education:


Clearly those who seek out (unpaid) work in education, compared to those who don't, are less tolerant of teen sex. Education volunteers are half as likely to say that it's merely "sometimes wrong" or "not wrong at all." This mirrors the belief pattern of adults who have varying numbers of teenagers in their household:


So, those who have greater day-to-day interaction with teenagers, whatever the reason, are less tolerant of them having sex. Adults are more likely to have a "let the kids be free" attitude if they don't get daily reminders of how young people actually behave. Those who seek out education work, then, are motivated to be guardians or something similar to parents, not by ulterior motives. An alternative explanation is that these more intolerant views are defense mechanisms so that their minds "don't even go there," preventing them from viewing their charges as potential mates.

The picture doesn't change if we throw the volunteer's sex into the mix. A multiple regression that predicts tolerance by sex and volunteering shows that women and education volunteers are less tolerant. In this model, the effect of sex is statistically significant, and the effect of volunteering in education is marginally significant (p = 0.064). There are only 243 volunteers, so presumably if we had a larger sample size, the p-value would dip below the arbitrary 0.05 level.

The most likely reason for the stereotype of the pervert who seeks out work with young people is what psychologists call the availability bias -- we think events are more likely if we can remember examples of them more easily. Given that we have little direct experience with people who work in education, we rely on news stories, whether from the mass media or spread by word-of-mouth. The cases where the teacher and soccer coach behave themselves don't merit any attention; it's only when they do something unseemly that we talk about working in education and being a pervert. Emotionally charged events like that also stick better in memory, as opposed to bland examples of well behaved teachers and coaches.

Since it's easier for us to recall examples of a teacher or coach who acted like a perv, we think that that's more likely for them than for someone with a job not involving young people. This is another reminder of the value of checking the data rather than relying on our impressions.

GSS variables used: teensex, voleduc, teens, sex

How are religiosity and teen pregnancy related?

Razib points me to a new study showing that, controlling for various factors, states with greater religiosity scores tend to have higher teen birth rates. So, compared to more secular states, the states in the Bible Belt are more likely to supply underage guests for the Maury Povich show who shout at their parents and the audience that, "I don't care what you think -- I'm gonna have that baby!"

But does this state-level pattern hold up at the individual level or not? To be clear what the question is, it could be that it's primarily the non-religious girls who give birth as teenagers -- say, because both traits reflect an underlying wild child disposition -- and perhaps the religiosity of their community is a response to tame this problem. So, for whatever reason, some states might have a greater fraction of devil-may-care girls, which would cause the state to have a higher teen birth rate as well as a greater religiosity score. (These states would have more of a teen pregnancy problem to deal with, hence a greater community policing response via religion.)

Or the patterns could be the same at the individual and the state levels -- that is, there's something about a highly religious life that makes a female more likely to give birth. For instance, if they thought it was their religious duty to be fruitful and multiply, or if they saw something sacred or divine in conceiving and giving birth -- rather than view it as a threat to their material or career success -- then the more religious teenagers would have higher birth rates.

To answer this, I went to the General Social Survey, which has data on individuals. There is no variable for age at first birth, so I simply created a new variable which is the year of the first child's birth minus the year of the mother's birth. Unfortunately, this restricts the data to just one year, 1994. Still, that was before the teen pregnancy rate had really plummeted, so there should be enough variety among those who gave birth as teenagers for any patterns to show up. In order to get larger sample sizes, I grouped female respondents into four categories for age at first birth: teen mothers (9 to 19), young mothers (20 to 24), older mothers (25 to 29), and middle-aged mothers (30 to 39).

A lot of the questions about religion were not asked in 1994, but I managed to find three each for religious beliefs and religious practice. For beliefs, the questions measure whether she has a literal interpretation of the Bible, how fundamentalist she is (now and at age 16), and whether she supports or opposes a ban on prayer in public schools. For practice, the questions measure how often she attends religious services, how strong her affiliation is, and how often she prays. (See note [1] for how "rarely," "occasionally," and "frequently" are defined.)

First, let's look at how religious beliefs vary among women who gave birth first at different ages:


The pattern is stark: the earlier she had her first child, the stronger her religious beliefs, whether that means Biblical literalism, fundamentalism (now as well as at age 16), or opposing a ban on prayer in public schools.

Now let's look at how religious practice varies:




Here the story is a bit different. Teen mothers have lowest religious attendance, although young mothers have the greatest, while older and middle-aged mothers are in between. Also, teen mothers are tied with middle-aged mothers for lowest religious affiliation, whereas the young and older mothers have more strongly affiliated women. The pattern for prayer is the same as for attendance: teen mothers pray the least often, while young mothers pray the most, with the older and middle-aged mothers in between.

Putting these two sets of results together, we see that both of the plausible explanations for the state-level pattern show up at the individual level. Teen mothers are more delinquent in their religious practice, which supports the view that they have some basic wild-child personality that influences their attitudes toward giving birth and going to church. However, we know it cannot be some underlying antipathy toward religion that causes them to miss church or prayer because they are actually the most likely to hold fundamentalist or literalist beliefs. That supports the view that there's something about having a strong personal religious conviction that gives them a more favorable view of conceiving and giving birth.

Thus, the overall profile of a teen mother is a girl who is passionate enough in her religious beliefs that she sees something wonderful in giving birth, even at such a young age, but whose lower degree of conscientiousness keeps her from performing the institutional rituals as often as she should. Not being so well integrated into the institution, she doesn't feel whatever dampening effects the institution may have exerted through peer pressure (for lack of a better term). Indeed, if you've ever seen one of those teen mother episodes of Maury Povich, this portrait should be eerily familiar -- a misfit who isn't going to change her behavior just to lessen the authorities' social disapproval (whether her parents, Maury, or the jury in the audience), but who finds fulfillment in her private faith and in the ineffable bond between her and her child.

[1] For attendance, "rarely" is never, less than once a year, or once a year; "occasionally" is several times a year, once a month, or 2-3 times a month; and "frequently" is nearly every week, every week, or more than once a week. For prayer, "rarely" is less than once a week or never; "occasionally" is several times or once a week; and "frequently" is once or several times a day.

GSS variables used: sex, kdyrbrn1, cohort, bible, fund, fund16, prayer, attend, reliten, pray.

What predicts income dissatisfaction?

Let's test the idea that as people attain higher status, they believe that their income is increasingly not enough to cover their expenses -- after getting that big promotion and moving to a better neighborhood, you've got more income, but it sure seems like life is more expensive, what with the private tutors and sports coaches for your kids, higher home prices, replacing the IKEA furniture with stuff from Crate & Barrel, etc. Life felt more affordable before.

The General Social Survey asks the following question:

Do you feel that the income from your job alone is enough to meet your family's usual monthly expenses and bills?

Note that the wording does not refer to things in the "take only what you need to survive" category. If you pay for tutoring, that's a usual monthly expense. If you go out to McDonald's several times a month, that's a usual monthly expense. So it's referring to whether the person's income is enough to support their broader lifestyle.

If the above idea is right, the percent who answer Yes should decline as we go up the status scale. In fact, the effect should be especially strong since this question was only asked in 2002 and 2006 -- right before the recent boom, and then during the height of the boom. People were furiously maxing out their credit cards, and they were surrounded by other people with lots of cool new stuff that they bought using maxed out credit cards. A feeling of income inadequacy at the higher status levels should have been particularly acute.

Out of curiosity, I also checked to see how income dissatisfaction varied within other demographic groups. Here are the results (click to enlarge):



The lowest income groups are the least satisfied, although once family income hits $20,000, dissatisfaction stays pretty constant. However, the very rich actually feel even more satisfied than other income groups. The same pattern holds for job prestige (socioeconomic index), education level, and self-reported economic class. Income dissatisfaction is basically constant across IQ levels (the lowest levels, 0 - 2, show funny results because of very small sample sizes). So, there is no evidence that higher-status people -- however measured -- are more bitter about their income level than lower or middle-status people. Quite the opposite.

As for age, surprisingly there is no big change from the college years through middle age, although by the time people are in their 60s, they are a bit more satisfied than before -- perhaps due to the falling need for social preening and oneupsmanship by then. Before then, though, more than 50% of each age group feels inadequate -- just unhappy in its own way (not getting a hot car when young vs. not finding a nice home when older).

Also surprisingly, there are are no race differences at all. We might have expected whites to feel more satisfied since they score higher on average for the above measures of social status. I fooled around by restricting the social status variables to the higher end or lower end, and it didn't seem to matter -- blacks and whites were still basically dead even. What they spend their money on may differ, but no racial group feels more or less satisfied than any other.

Finally, there is a gigantic sex difference, dwarfing anything else we've seen. While 57% of men are satisfied with their income, only 34% of women are. We can't attribute this to women wanting to shop more, or for more expensive things -- men have their eyes on super-expensive cars and other auto-related junk, amateur sports equipment, big flashy gadgets and electronics, and so on. And men don't make that much more than women, so it can't be due to differences in income. I think it must be a personality difference rooted in the brain's wiring. In questionnaires, women consistently score much higher on the personality trait Neuroticism than men. And this shows up in the real world, as they suffer more from depression than men. The feelings of anxiety, self-doubt, and impulsiveness that characterize Neuroticism should show up when we ask people if they're satisfied with their income level.

These other demographic findings are pretty neat, but the most robust and important finding is that income dissatisfaction does not increase as you move up the status scale. We may have this misperception because those higher-status people who are not satisfied are the ones most likely to speak up about it, and the ones who the media are most likely to cover because of the schadenfreude value it provides the readers with. No one wants to write or read a news feature on a bunch of people who say, "I'm rich and educated -- and it is all it's cracked up to be!"

GSS variables used: rincblls, race, sex, age, class, sei, wordsum, educ, realinc

Brief: Relationship anger by political views for men and women

The stereotype is that liberal women are more combative and temperamental in relationships, compared to the more docile and even-headed conservative women. Let's take a look at the GSS and see if it's true. We'll look at the same question for men.

The survey asks about some recent event when the respondent was angry, and it follows up to ask who they were angry at. I pooled all three degrees of liberal, and all three degrees of conservative, to get roughly equal sample sizes for liberal, moderate, and conservative. The pattern is clear even without doing this, but this is to make the presentation easier. Here are the results (the y-axis should read "fraction angry," not "% angry"):


First, note that women are about twice as likely to be angry at their relationship partner than are men. No surprise there. Also note that the pattern by political views isn't so different between the sexes. Among females, moderates and conservatives aren't really different from each other, but both are twice as likely as liberals to get angry at their partner. Among males, moderates and conservatives are about 1.5 times as likely as liberals to get angry at their partner.

There are a million different ad hoc reasons I could give for why the stereotype isn't true, but I'd have no way of verifying them with just these data. Whatever the cause, liberal women are actually a safer bet if you're looking for peace in the relationship.

GSS variables used: madat1, polviews, sex

The changing social climate of young people from 1870 to present

[This will end up being quite long, so I will post it in three stages for easier digestion. Expect two updates during the week. First update on generations added.]

OK, so the title is a bit ambitious, but I've finally found a way to measure this. Anyone who's read my personal blog knows that one of my obsessions is documenting what's going on among young people. They typically leave very little in terms of a written record, and as adults most people erase the memories of their adolescence -- to the benefit of their mental health -- and replace them with whatever accords with their grown-up worldview. For example, they may imagine adolescents as relatively innocent creatures, whereas their memories -- if unearthed -- would remind them of what an anarchic jungle secondary school was, in contrast to the much more tranquil social lives of adults.

So, the need for a clearer picture of young people's lives is great, yet clearly unmet. As luck would have it, The Harvard Crimson (the undergraduate newspaper) has placed all of its content online, stretching back to the paper's origin in 1873, and it is fully searchable. This allows me to search for some signal of the zeitgeist year by year and plot the strength of this signal over time. If you read my three-part series at GNXP on the changing intellectual climate, as judged by what appears in academic journals, the approach is the same. (Here are those articles: Death of Marxism, etc., A follow-up, and Popularity of science in studying humans.)

In short, I count the number of articles in a given year that have some keyword -- "Marxism," for example -- and then standardize this by dividing by a very common neutral word. This protects against seeing an imaginary trend that is simply due to the newspaper pumping out many more articles over time (or fewer in hard times). Ideally, I would standardize by using "the" since it appears in every article and therefore gives us the total number of articles, answering the question "What percent of all articles in that year contained this keyword?" Unfortunately, the Crimson search engine won't allow me to use "the," but it did let me search for "one," which is also a highly frequent word and will be a decent substitute. Before getting into the meat of the post, here is the number of articles found by searching for "one" across time:


We were correct to standardize somehow, given the huge increase since the early 1990s (probably reflecting the greater ease of desktop publishing with cheap computers and software).

A real improvement over the previous series that used JSTOR is that the Crimson archives run right up to the present, whereas JSTOR typically has a 5-year lag between the article's being published and being archived in JSTOR. The only limitation here is that we only see what's going on among upper-middle class young people, rather than all of them, but I'm mostly looking at events or topics that permeate our society, rather than academic fads as before. (Although I will probably look into that as well using the Crimson database.) So these youngsters ought to be fairly representative.

Moving on to the substance, I've put together graphs on three broad topics that are of great importance to young people. Adults also tend to worry about where the next generation stands on these topics. They are identity politics, religion, and generational awareness.

Identity politics

Everyone knows that the 1960s brought a sea change in college student culture, but I don't think anyone has presented a clear picture of how the concern with racism, sexism, etc. began or how it has changed over time to the present. In particular, most people (in my experience) over-estimate how prevalent identity politics were in the '60s, while forgetting how widespread the corresponding hysteria was in the early 1990s.

I began at the earliest date that the word appears or 1960, whichever came first, and end in 2008. The y-axis shows the count of articles with the keyword divided by the count of articles with "one." I chose the following identity politics keywords: "racism" or "racist," "sexism" or "sexist," "homophobia" or "homophobic," "date rape," and "hate speech." I also made a composite which sums all of them up. Here are the results:


"Racism" increases sharply through the '60s, peaks in 1970, and declines moderately through the '70s and '80s. However, starting in the late '80s, there's another surge which peaks in 1992. After the early '90s panic, though, the preoccupation with racism has declined substantially, so much so that it is now back down to its pre-late-'60s level. You'll recall how little widespread disruption there was in the wake of Hurricane Katrina, the Jena Six, and the Duke lacrosse hoax, despite every professional activist -- and even Kanye West on a televised awards show -- struggling to whip up society into another revolution. But 2006 had none of the racial hysteria to fuel it that 1992 did, so it was impossible to spark another round of race riots in L.A.

As for "sexism," it only begins in 1970. Many people who weren't alive back then don't remember how little of a role women's liberation played in The Sixties. But I used to be a radical activist in my naive college days, and Z Magazine operator Michael Albert emphasized that second-wave feminism was largely a delayed response to the perceived sexism of the anti-war, civil rights, and anti-capitalist movements that formed the basis of the counter-culture's concerns. Although there is not much change during the '70s and '80s, it got a pretty high jump initially, so it's not as though there were few adherents -- there just wasn't a massive increase. But once again, starting in 1988 there's a resurgence that peaks in 1992. This is when third-wave feminism was born, and it coincided with the resurgence of racial politics.

However, just as with race, panic about sex plummeted shortly afterward and is currently even lower than its initial level. Again, recall how few massive protests there were -- if any -- about the Duke lacrosse hoax, whose bogus premise was a bunch of jocks raping a stripper. Or for that matter, how pathetic the response was to the Larry Summers brou-ha-ha of early 2005. It surely generated some controversy among academics, but even that didn't last very long, and no one outside of academia gave a shit. In particular, the students didn't care -- influence from their leftist professors notwithstanding. If the zeitgeist lacks an obsession with sex roles, their feminist professors can preach all they want, but it will only fall on deaf ears.

Paying attention to homophobia only begins in 1977 -- 8 full years after the Stonewall Riots. And remember, that was in 1969, a ripe time for liberationist and revolutionary movements. This underscores the importance of using quantitative data in reconstructing history, since most people nowadays would imagine that back in the turbulent '60s, they were surely fighting against homophobia the way that their counterparts do now. Far from it. Back in the '60s, and even for most of the '70s and early '80s, campus radicals and liberals couldn't have cared less. Again, back then it was all about civil rights, stopping the imperialist war machine, and maybe smashing capitalism -- not about gay marriage or getting more women into science careers.

As we saw with "racism" and "sexism," "homophobia" saw a sharp rise in the late '80s and peaked in 1989 or '90, before dropping precipitously afterward. Currently it is more or less where it was before the late '80s surge. Liberals and young people may support gay marriage, but the larger meta-narrative of homophobia, as the activists would say, does not interest them.

Now we come to two more specific topics. "Date rape" basically tracks third-wave feminism, although there is an isolated occurrence in 1979 (which I exclude from the graph to keep the trend clear). Quite simply, there is rape and there is not-rape. "Date rape" was a term that tried to criminalize sex that wasn't rape, but where the girl regretted it or was unsure of what was happening. Probably the guy was stinking drunk too. Importantly, claims about "date rape" drugs later turned out to be bogus, as doctors in the UK pointed out -- most of the women claiming to have been slipped a "date rape drug" had no such drug in their system, although they typically did have lots of alcohol or other hard drugs present. It was essentially a witch-hunt or moral panic. By now, we know what to expect -- a sharp rise during the late '80s that peaks in 1992 and falls off a cliff shorter thereafter. Nowadays no one takes the idea seriously.

"Hate speech" shows roughly the same pattern, although it doesn't get started quite as early. It appears suddenly in 1990, peaks in 1991, and plummets right away. Aside from an anomalous jump in 2002 - '03 (which may reflect some event specific to Harvard), it has remained very low for nearly 15 years. Compared to college students during the heyday of Generation X back in 1991 - '92, young people today are more likely to view the concept of "hate speech" as a thinly veiled attempt to censor unpopular viewpoints.

It's interesting to note the differences in scale among the five topics. The "racism" scale is 3 times as great as those for "sexism," "homophobia," and "date rape," confirming what many others have observed -- that in the struggle for a bigger piece of the identity politics pie, race has trumped sex or sexuality. The scale for "hate speech" is about 3 times smaller than the previously mentioned three topics, perhaps because it is so specific, while "racism" pops up in many more contexts.

The composite identity politics index shows roughly the same pattern that we've noted before. There's a jump during the '60s which peaks in 1970 -- this only reflects a concern with racism. There is little or slightly negative growth during the '70s and '80s, but this was only the calm before the storm. In the late '80s, another wave of panics sweep through, and there is a sustained peak from 1989 through 1992. I have often pointed out in my personal blog and less often at GNXP that the peak of the social hysteria is 1991 - 1992, and this confirms that claim.

As with other epidemics, eventually it burns out, and obsessing over identity politics is now at or below its pre-late-'60s level. This overall pattern does not change even if I remove the two topics of "date rape" and "hate speech" that might seem to bias things toward producing an early '90s peak. Hard as it may be to believe for anyone younger than the Baby Boomers, identity politics was simply a very small piece of the radical chic calling back in the '60s -- it was about civil rights, anti-war, and capital.

Generational awareness

We often speak of young people as an entire generation, but that only works when they have strong generational awareness or solidarity. Otherwise, they are merely a cohort. To give a personal example, I am too young to be part of Generation X, yet I'm a bit older than the Millennials. Almost no one my age (roughly mid-late 20s) is stuck in the culture of their adolescence and college years and never will be, in the way that many Baby Boomers are culturally stuck in 1968 and many Gen X-ers are stuck in 1992. It is possible to be a traitor to your generation if you're a Boomer or X-er, but since my cohort doesn't view itself as a Generation, the idea of defecting fails to make sense.

The same goes for the cohort born between roughly 1958 and 1964 -- their age-mates will not burn them at the stake for saying that they never liked disco music or punk rock, unlike a Boomer who said he didn't like the Beatles' later albums or a Gen X-er who said he always thought alternative rock was lame.

In any case, how do we quantify this sentiment? I simply searched the Crimson for "generation," which will turn up any time a member of a Generation writes about their age-mates as though they were a cohesive group, as well as when older people recognize the young people of today as being different and a cohesive group. I assume that its secondary use as a synonym for creation is roughly constant over time, so that changes reflect its primary use. The counts for the very early years are low, and the number of articles with "one" is also low, so I'm not so sure that the standardized measurement is telling us something real for that time period. Thus, along with the standardized graph, I've included one that shows just the counts. Here are the results:


The trendline is exponential, although other simple trends show roughly the same picture. It seems that during Gilded Age and Progressive Era, thinking in generational terms was not very common, although it does turn up toward the end of the Progressive Era. I'll get to my conjecture about this after surveying the other periods.

During the Roaring Twenties and through the Great Depression and WWII, the level is much greater than the historical trend and lasts very long. This may strike us as unexpected because we associate inter-generational conflict mostly with the late 1960s -- but if you thought young people were going crazy then, you should have seen them during the 1920s! Women started driving, smoking, swearing, and cutting their hair short like men -- take that, you dinosaurs! Jazz and later swing were just as much of a middle finger to older people as rock and roll was later on -- perhaps more so, given how much jazz broke with other forms of popular and classical music that formed the cultural background. Rock and roll, compared to its background, wasn't so different. One central way by which young people mark themselves off from older people is by inventing their own slang, and they indeed made a bunch of it in the 1920s, much of which is still with us today.

After WWII and through the first half of the 1960s -- the Golden Age of American Capitalism -- the level dips below the historical trend. The name "Silent Generation" was coined in 1951 to refer to young people at the time, and silent they were. If we must use "generation" instead of cohort, I prefer using distinct names for what I've been calling Generations -- Boomers, X-ers, etc. -- and numbered Silent Generations for everyone else (i.e., Silent Generation 1, 2, 3, ...). Of course, after them come the Baby Boomers, although surprisingly the late '60s level is not so far above the historical trend. Still, in absolute terms, it's as high as it was during the 1920s, even if it doesn't last as long.

There is a dip below trend for most of the 1980s, when Silent Generation 2 was in college. Then there's a spike in the early 1990s, reflecting Generation X finding its megaphone, to everyone's annoyance. It's hard to make out the end -- it looks mostly at the historical trend, perhaps with a recent jump. Sometime in the middle of the next decade, we'll be hit by another wave of social hysteria, and that will crystallize the young people then (say, age 16 to 24) into a new generation. We already have a name for them -- the Millennials -- but their generational self-awareness doesn't seem very deep to me right now. Voting for Obama has been the extent of them making us hear the voice of a new generation. But just wait.

I'm not too sure what causes the increasing historical trend -- maybe it just shows that the word is becoming more and more common to describe something we already talked about before, and hence the trend isn't interesting. Or it could mean that with an increasing pace of cultural change, we are able to pay better attention to generational changes, and we can therefore talk about them a lot more than before.

What's really interesting are the oscillations above and below the trend, which correspond pretty well to what we consider the heydays of Generations and Silent Generations, respectively. Trying to piece it all together, I think that generational awareness is low when times are prosperous and young people are small as a fraction of the population. This combination of good economic times and little competition means they can more easily establish themselves during early adulthood on their own. They don't feel gipped or embittered, so they aren't anti-establishment (which in practice means anti-elders). In contrast, when economic times are bad and there are a lot of young people competing to establish themselves, anxiety about the future sets in, many feel cheated -- they went to college and didn't end up making it rich -- and they have to band together to support each other.

This is really just a rough guess, and I don't have good data to present on the percent of the population that's 16 to 24, or what their average wages were, over this entire time period. And there are exceptions, of course. But looking at the whole thing, that's what I see.

Next update: religion, which will cover five topics and include a composite index.